Diagnostic accuracy of low-mA chest CT reconstructed with Model Based Iterative Reconstruction in the detection of early pleuro-pulmonary complications following a lung transplantation.
Objectives: To assess the accuracy of reduced-dose, low-mA chest CT (RD-CT) reconstructed with model-based iterative reconstruction (MBIR) in detecting usual early complications following pulmonary transplantation, as compared to standard-dose chest CT (SD-CT) reconstructed with adaptative statistic...
| Publicado en: | European Radiology Vol. 26; no. 9; pp. 3138 - 3147 |
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| Autores principales: | , , , , , , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Springer Nature
Sep2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=117171336&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 117171336 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: Sep2016 vid: 26 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 117171336 117171336 NLM26645864 117171336 10.1007/s00330-015-4126-0 NLM26645864 117171336 ppf: 3138 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Diagnostic accuracy of low-mA chest CT reconstructed with Model Based Iterative Reconstruction in the detection of early pleuro-pulmonary complications following a lung transplantation. aug: au: Debray, Marie-Pierre Dauriat, Gaëlle Khalil, Antoine Leygnac, Sebastien Tubiana, Sarah Grandjean, Albane Schouman-Claeys, Elisabeth Laissy, Jean-Pierre Ou, Phalla affil: Department of Radiology , AP-HP, Bichat-Claude Bernard Hospital , Paris France sug: subj: Pleura Tomography, X-Ray Computed Methods Lung Diseases Diagnosis Lung Radiography, Thoracic Methods Pleural Diseases Diagnosis Lung Transplantation Adverse Effects Algorithms Models, Theoretical Male Radiation Dosage Female Middle Age Prospective Studies Adult Human Middle Aged: 45-64 years Adult: 19-44 years Male Female ab: Objectives: To assess the accuracy of reduced-dose, low-mA chest CT (RD-CT) reconstructed with model-based iterative reconstruction (MBIR) in detecting usual early complications following pulmonary transplantation, as compared to standard-dose chest CT (SD-CT) reconstructed with adaptative statistical iterative reconstruction (ASIR).Methods: Our institutional review board approved this prospective study and patients provided written informed consent. Two thoracic radiologists independently evaluated 47 examinations performed routinely in 20 patients during 6 months following lung transplantation for the detection and/or evolution of usual pleuropulmonary complications and for subjective image quality. Each examination consisted of successive acquisition of unenhanced SD-CT (100-120 kV, noise index 45, ASIR) and RD-CT (100 kV, 16-24mAs/slice, MBIR).Results: Mean CTDIvol was 4.12 ± 0.88 and 0.65 ± 0.09 mGy for SD-CT and RD-CT, respectively. Complications were found in 40/47 (85 %) examinations. Sensitivity and negative predictive value of RD-CT were 92-100 % for the detection of pneumonia, fungal infection, pleural effusion, pneumothorax, and bronchial dehiscence or stenosis, as compared to SD-CT. Image quality of RD-CT was graded good for 81 % of examinations.Conclusions: MBIR-RD-CT is accurate, as compared to SD-CT, for delineating most usual pleuropulmonary complications during the 6 months following pulmonary transplantation and might be used routinely for the early monitoring of pulmonary allografts.Key Points: • Early chest complications are frequent following a pulmonary transplantation • CT has a key role for their detection and follow-up • Low-mAMBIR CT is accurate for monitoring most lung allograft early pleuropulmonary complications • MBIR chest CT allows a six-fold dose reduction compared to standard CT. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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